Financial trading has been widely analyzed for decades with market participants and academics always looking for advanced methods to improve trading performance. Deep reinforcement learning (DRL), a recently reinvigorated method with significant success in multiple domains, still has to show its...

Peer-to-Peer (P2P) fintech platforms allow cost reduction and service improvement in credit lending. However, these improvements may come at the price of a worse credit risk measurement, and this can hamper lenders and endanger the stability of a financial system. We approach the problem of...

From 2004 to 2015, the market perception of the sovereign risks of the Euro area government bonds experienced several different phases, reflected in a clear time structure of the correlation matrix between the yield changes. "Core" and "peripheral" bonds cluster in a bloc-like structure, but the...

In this paper, we present a framework for detecting distinct correlation regimes and analyzing the emerging state dependences for a multi-asset futures portfolio from 1998 to 2013. These correlation regimes have been significantly different since the financial crisis of 2008 than they were...

As cryptocoins are not tied to fundamental values or to investor protection regulation, their price dynamics is unhinged in both directions. In institutional asset management of conventional asset classes, target volatility concepts and dynamic allocation heuristics are popular to improve the...

In this paper, the authors construct a pipeline to benchmark Hierarchical Risk Parity (HRP) relative to Equal Risk Contribution (ERC) as examples of diversification strategies allocating to liquid multi-asset futures markets with dynamic leverage ("volatility target"). The authors use...